Weakly supervised violence detection in surveillance vídeo.
dc.contributor.author | Choqueluque Roman, David | |
dc.contributor.author | Cámara Chávez, Guillermo | |
dc.date.accessioned | 2023-07-24T20:01:04Z | |
dc.date.available | 2023-07-24T20:01:04Z | |
dc.date.issued | 2022 | pt_BR |
dc.description.abstract | Automatic violence detection in video surveillance is essential for social and personal security. Monitoring the large number of surveillance cameras used in public and private areas is challenging for human operators. The manual nature of this task significantly increases the possibility of ignoring important events due to human limitations when paying attention to multiple targets at a time. Researchers have proposed several methods to detect violent events automatically to overcome this problem. So far, most previous studies have focused only on classifying short clips without performing spatial localization. In this work, we tackle this problem by proposing a weakly supervised method to detect spatially and temporarily violent actions in surveillance videos using only video-level labels. The proposed method follows a Fast-RCNN style architecture, that has been temporally extended. First, we generate spatiotemporal proposals (action tubes) leveraging pre-trained person detectors, motion appearance (dynamic images), and tracking algorithms. Then, given an input video and the action proposals, we extract spatiotemporal features using deep neural networks. Finally, a classifier based on multiple-instance learning is trained to label each action tube as violent or non-violent. We obtain similar results to the state of the art in three public databases Hockey Fight, RLVSD, and RWF-2000, achieving an accuracy of 97.3%, 92.88%, 88.7%, respectively. | pt_BR |
dc.identifier.citation | CHOQUELUQUE ROMAN, D.; CÁMARA CHÁVEZ, G. Weakly supervised violence detection in surveillance vídeo. Sensors, v. 22, n. 12, artigo 4502, 2022. Disponível em: <https://www.mdpi.com/1424-8220/22/12/4502>. Acesso em: 06 jul. 2023. | pt_BR |
dc.identifier.doi | https://doi.org/10.3390/s22124502 | pt_BR |
dc.identifier.issn | 1424-8220 | |
dc.identifier.uri | http://www.repositorio.ufop.br/jspui/handle/123456789/17044 | |
dc.language.iso | en_US | pt_BR |
dc.rights | aberto | pt_BR |
dc.rights.license | This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). Fonte: PDF do artigo. | pt_BR |
dc.subject | Spatiotemporal violence detection | pt_BR |
dc.subject | Dynamic image | pt_BR |
dc.title | Weakly supervised violence detection in surveillance vídeo. | pt_BR |
dc.type | Artigo publicado em periodico | pt_BR |
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